Title :
Reducing Soot Emissions in a Diesel Series Hybrid Electric Vehicle Using a Power Rate Constraint Map
Author :
Youngki Kim ; Salvi, Alessandro ; Stefanopoulou, Anna G. ; Ersal, Tulga
Author_Institution :
Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
This paper considers a diesel series hybrid electric vehicle (SHEV) and proposes the utilization of an engine-generator power rate constraint map to reduce soot emissions without a significant compromise in fuel economy. Specifically, model predictive control (MPC) is used to split the vehicle power demand between the engine-generator unit and the battery. To achieve a reduction in soot, the engine-generator power rate is constrained. Unlike existing strategies, the power rate limit is not a fixed value but varies, depending on the power level, resulting in a map. This constraint map is designed by formulating the soot emission reduction problem as an optimization problem, which is solved through a three-step offline discrete optimization process. The optimization relies on a quasi-static soot emissions map that captures the trends, even during transients, but underestimates the magnitudes. Therefore, to evaluate the performance of the MPC-based power management with the power rate constraint map, experiments are conducted through an engine-in-the-loop simulation framework. Experimental results show that compared with a constant power rate constraint, soot emissions can be reduced by 44.5% while compromising fuel economy by only 0.3% through the proposed approach. As a tradeoff, the ampere-hour (Ah) processed in the battery, which is a variable that has been shown to correlate with battery capacity loss, increases by 5.5%.
Keywords :
air pollution control; battery powered vehicles; diesel engines; fuel economy; hybrid electric vehicles; optimisation; power control; predictive control; soot; MPC; MPC-based power management; SHEV; battery; diesel series hybrid electric vehicle; engine-generator power rate constraint map; engine-in-the-loop simulation framework; fuel economy; model predictive control; optimization problem; quasistatic soot emissions map; soot emission reduction; three-step offline discrete optimization process; vehicle power demand; Batteries; Engines; Fuel economy; Generators; Optimization; System-on-chip; Vehicles; Diesel engines; discrete optimization; model predictive control (MPC); power management; series hybrid electric vehicles (SHEVs); soot emissions;
Journal_Title :
Vehicular Technology, IEEE Transactions on
DOI :
10.1109/TVT.2014.2321346